libproxyprotocol
neat-matrix-library
libproxyprotocol | neat-matrix-library | |
---|---|---|
2 | 7 | |
11 | 87 | |
- | - | |
2.2 | 2.2 | |
about 1 year ago | 3 months ago | |
C | C | |
GNU Lesser General Public License v3.0 only | Apache License 2.0 |
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libproxyprotocol
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An ANSI C library to parse and create PROXY protocol v1 and v2 headers with support for all TLVs including the custom ones from AWS and Azure
Github project: libproxyprotocol
- An ANSI C library to parse and create PROXY protocol v1 and v2 headers with support for all TLVs including the custom ones from AWS and Azure. Full coverage of the latest 2.6 specification. Any feedback is appreciated
neat-matrix-library
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Quick question: Care e faza cu a fi crab?
Cu C mă joc că hobby: * https://github.com/nomemory/neat-matrix-library
- On writing your own linear algebra matrix library in C (follow-up article with explanations after submitting the github library a while back)
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As a hobbyist, I've written my own matrices library in C
I am a math hobbyist, and I wanted to work on my linear algebra knowledge. So I've decided to implement some of the most common algorithms from the CS curricula.
After some work, I've come-up with this small library. It has no production value, but it was fun learning experience.
https://github.com/nomemory/neat-matrix-library
- Proiectele open source la care am lucrat în ultimă perioada
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My first deep-dive into linear algebra and numerical analysis. An article describing how to write a C library that performs most of the "academical" algorithms for matrices (Row Echelon, Reduced Row Echelon, LU(P) Factorization, Inverse, Determinants, etc.)
And the resulting code corresponding to the article can be found here: https://github.com/nomemory/neat-matrix-library
- Got back to C after a few years, and created my first C library: NML is a simple matrix library that implements various numerical analysis algorithms (Gauss Elimination, Gauss-Jordan, Gram-Schmidt, LU(P) Factorisation, etc.)
- One of my C projects: NML - a simple matrix library supporting various (LU Decomposition, Gauss Elimination, Gauss-Jordan, Gram-Schmidt, Inverse, Determinant). Any feedback is greatly appreciated.
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